Google Shopping & Rule Based Bidding
Unfortunately, a lot of advertisers don’t utilize rule-based bidding strategies to optimize their Google Shopping campaigns as much as they should.
Many times, advertisers think Shopping is just a ‘set it and forget it’ type of management. Typically, your two best performers are going to be trademark campaigns (aka branded traffic) and Google Shopping because they represent the bottom of the funnel.
“But, whenever we do an audit of a Shopping campaign, we usually end up finding a lot of wasted spend and the potential for opportunity,” David Weichel, VP Product Development at CPC Strategy said.
“What has worked really well for us is to start with a set of bid rules for introducing ourselves to the product catalog.”
“And yes- every catalog is going to work a little bit differently, but over time what we can do (as a result of rule-based bidding) is better understand the way your inventory and products adjust to bid changes or manual actions we are taking.”
“This has been a successful approach to quickly being able to show impact on performance.”
With rule-based bidding you can be very specific and customize your inputs, as opposed to algorithmic bidding – which can be a ‘cookie cutter’ type software that has to be able to work for businesses of all different shapes and sizes.
Your business is unique and marketing managers should have access to the ability to build their own customized rules to fit their business needs.
If applied correctly, rule-based bidding technology can help retailers streamline their bidding process, save time, and optimize product-level campaign management and efficiency.
Google Shopping Rule-Based Bidding
1) Pulling Back on Wasted Ad Spend:
This rule impacts any items with zero conversions, (ex: cross device conversions or direct on site conversions – depending on your campaign objectives). The rule is implemented to pull back on items that are above a certain spend threshold, over a certain number of days.
Any entity that remains above that spend threshold – that’s essentially not contributing to your top line will be pulled back.
According to Weichel, this should be running in the background to ensure that your wasted ad spend doesn’t get carried away.
“A caveat to that rule – is that you can start stealing away traffic or visibility from the top of the funnel. But for the most part, that top of the funnel (prospecting type of traffic) will be segmented into a separate campaign, so you can very easily partition that traffic out.”
This bid rule tackles several objectives by increasing efficiency of campaigns by reducing wasted ad spend, and allowing us to reallocate that same budget into higher converting, more profitable traffic.
2) Bid Increase Rule(s):
The bid increase rule is for converters to gain more visibility. We bucket these bid increases into 3 classes including “mid-range” converters, “top” converters, and “one-off” converters.
You can create a simple filter to look at repeat converters. For example – over a standard lookback period of 30 days, anything with 2 or more conversions, that meet your cost of sales goal – the rule will increase the bid on those items. Say your cost of sales goal is 4:1, then every item that is 5:1 and better (with repeat conversions of 2 or more) , we will increase the bid 5% or 2% (depending on how high your bids are).
So, now let’s take a look at the top converters or best converters. (You can think of top converter items as the higher ROAS products, these are our “10x-ers” or unicorns.) Advertisers can apply that same repeat conversions filter that we mentioned above for the mid-range converters. What this is going to do (especially if the mid-range and top converters are running at the same schedule) is create a compounding effect (also what we refer to as “stacking”). Bid rule stacking can help advertisers capitalize if implemented correctly.
“One-off converters especially in retail, happen all the time,” Weichel said.
“Most of time these items are not getting much traffic (Example: for every 3 clicks, one conversion) despite at the surface level they look like a pretty healthy metric, but in reality it’s low volume.”
So, what the rule does is increase the bids. For example, our filters will be (conversions = 1), but those products also have to be profitable, and you might want to consider implementing a cost threshold.
“The bid increase for this type won’t be as aggressive as the top or mid-range converters because we have lower level of confidence in the one-off converts.”
3) Bump Products with Zero Impressions
This group will target products that get zero impressions over the last 30 days and historically have not had impressions. This is inventory we don’t typically push too hard – because it doesn’t demand a lot of our attention.
But the objective of the rule is to try and drive incremental revenue. For most catalogs, advertisers will push the majority of spend to the top converting products, which is expected, but that only covers a small range of the total catalog, typically anywhere from 5-20%. The rule will increase bids on individual products up until they hit a certain impression threshold.
“The whole point of this rule is to drive incremental growth via the rest of the catalog that doesn’t get much attention. Once these products gain impressions they’re healthy enough to compete in the auction and after collecting enough data they might qualify to be moved into a different bid group,” Weichel said.
4) Reduce Bid on Bleeders
Bleeders are defined as items that get conversions but are not considered profitable. One way to think of “bleeders” is that they are likely high performing items (when they convert) but in general they are kind of tough to deal with (lots of wasted ad spend), aka it costs too much to acquire the customer. For example, this could include items with a conversion or a ROAS less than 4. These are the items where we want to significantly decrease the bid.
How Does Rule Based Bidding Impact Efficiency & Growth?
“Retailers want both efficiency and growth for their campaigns but those two things are usually at odds. By focusing on the wasted ad spend (aka the non-converters) we are able to effectively do both in a way that is actually kind of surprising,” Weichel said.
“The bleeders are also really important for tugging on the efficiency lever, even though it sometimes impacts the volume. Additionally, the zero impression filter also help to promote growth by pushing more aggressively for products that we never used to before.”